Phosphorylation-dependent control of Activity-regulated cytoskeleton-associated protein (Arc) protein by Tnik
Bibliographic record
Abstract
The remarkable capacity of neurons to reorganize their structure, function, and connections in an activity-dependent manner is supported by an extensive network of molecules and effectors. Among those, the 'hub' protein Activity-regulated cytoskeleton-associated protein (Arc, also known as Arg3.1) can be considered one of the central, as well as most versatile, players. Notably, Arc has been shown to maintain direct interactions with key synaptic factors like PSD95, TARPγ2, and CaMKII, as well as participate in many aspects of neuroplasticity such as trafficking of AMPARs and modeling of dendritic spines. How a single protein like Arc can do all this remains difficult to explain, but a complete answer to that question will certainly include a mix of protein post-translational modifications acting to confer molecular and functional specificity. Recently, sequence analysis of Arc protein led us to recognize two candidate phosphorylation sites specific to TRAF2 and NCK-interacting protein kinase (TNIK)--a member of the Germinal Center Kinases (GCK) subfamily that is considered a possible risk factor to different psychiatric disorders, including schizophrenia and bipolar disorder. Here, we present extensive biochemical, proteomics, and electron microscopy evidence supporting the influence of TNIK on Arc's subcellular distribution and oligomerization. Together, our findings position Arc as a substrate of TNIK and offer exciting new scenarios implicating these two factors in the context of the pathophysiology and potential treatment of neuropsychiatric disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".